Survival Analysis Using SAS: A Practical Guide, Second Edition Paul D Allison SAS Publishing (2010)
Survival%20Analysis%20Using%20SAS_%20A%20Practical%20Guide
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- Contents
- Chapter 1 Introduction
- Chapter 2 Basic Concepts of Survival Analysis
- Chapter 3 Estimating and Comparing Survival Curves with PROC LIFETEST
- Chapter 4 Estimating Parametric Regression Models with PROC LIFEREG
- Introduction
- The Accelerated Failure Time Model
- Alternative Distributions
- Categorical Variables and the CLASS Statement
- Maximum Likelihood Estimation
- Hypothesis Tests
- Goodness-of-Fit Tests with the Likelihood-Ratio Statistic
- Graphical Methods for Evaluating Model Fit
- Left Censoring and Interval Censoring
- Generating Predictions and Hazard Functions
- The Piecewise Exponential Model
- Bayesian Estimation and Testing
- Conclusion
- Chapter 5 Estimating Cox Regression Models with PROC PHREG
- Introduction
- The Proportional Hazards Model
- Partial Likelihood
- Tied Data
- Time-Dependent Covariates
- Cox Models with Nonproportional Hazards
- Interactions with Time as Time-Dependent Covariates
- Nonproportionality via Stratification
- Left Truncation and Late Entry into the Risk Set
- Estimating Survivor Functions
- Testing Linear Hypotheses with CONTRAST or TEST Statements
- Customized Hazard Ratios
- Bayesian Estimation and Testing
- Conclusion
- Chapter 6 Competing Risks
- Chapter 7 Analysis of Tied or Discrete Data with PROC LOGISTIC
- Chapter 8 Heterogeneity, Repeated Events, and Other Topics
- Chapter 9 A Guide for the Perplexed
- Appendix 1 Macro Programs
- Appendix 2 Data Sets
- Introduction
- The MYEL Data Set: Myelomatosis Patients
- The RECID Data Set: Arrest Times for Released Prisoners
- The STAN Data Set: Stanford Heart Transplant Patients
- The BREAST Data Set: Survival Data for Breast Cancer Patients
- The JOBDUR Data Set: Durations of Jobs
- The ALCO Data Set: Survival of Cirrhosis Patients
- The LEADERS Data Set: Time in Power for Leaders of Countries
- The RANK Data Set: Promotions in Rank for Biochemists
- The JOBMULT Data Set: REpeated Job Changes
- References
- Index